Investigation of the Link Between Food Assistance Programs and Physical Activity Among Children and Adolescents
Bibliographic record
Abstract
Background: While the direct benefits of food assistance programs are well-documented, there is a need to explore indirect benefits like increased physical activity. This study examined whether participation in the Supplemental Nutrition Assistance Program (SNAP) was associated with improved physical activity levels in children and adolescents aged 2-17 in the United States during 2017-2018. Study Design: A cross-sectional study. Methods: This cross-sectional study used a subset of National Health and Nutrition Examination Survey (NHANES) data (n=2620). In the NHANES 2017-2018 dataset, physical activity was measured through self-report questionnaires, which captured participants’ frequency, duration, and intensity of various activities. We used weighted logistic regression and the Hosmer - Lemeshow - Sturdivant forward model - building strategy to investigate this hypothesized association using SAS version 9.4. Results: In the adjusted model, controlling for the other variables in the model, we found that children and adolescents from households that had received SNAP/Food Stamps had 1.53 times higher odds (odds ratio [OR]=1.53, 95% CI: 1.24-1.89) of achieving the recommended guidelines of 60 minutes of daily physical activity compared to those who had not received benefits. Each additional year of age resulted in 0.82 times lower odds (OR=0.82; 95% CI: 0.79, 0.85) of meeting the recommended amounts of physical activity. Additionally, each unit increase in BMI was associated with 0.96 times lower odds (OR=0.96, 95% CI: 0.93, 0.98) of engaging in recommended physical activity. Conclusion: These findings suggest that participation in the SNAP/Food Stamps program may indirectly benefit participants by increasing physical activity levels.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".